Search results for: efficiency analysis and selection bias

Authors: Shuo Liu, Dan Liu

Abstract:

In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

Procedia PDF Downloads 133

Authors: Thomas C. Nash

Abstract:

New Zealand has a small, yet racially diverse, population of only 4.6 million people, consisting of a majority European immigrant population and a large indigenous Maori population. Because disparities in healthcare often exist among minority populations, it could be expected that the White and Maori populations of New Zealand would have unequal access to healthcare. In order to understand the ways these disparities may present themselves, it became important to travel to New Zealand in order to interview both Western and natural healthcare professionals, public health officials, health activists and Maori people. In observing the various mechanisms within the New Zealand healthcare system, some stand out as effective ways of alleviating the racial disparities often seen in healthcare. These include the efficiency of regional District Health Boards, the benefits of individuals making decisions regarding their treatment plans and the importance of cohesion among the Maori and White populations. In forming a conclusion around these observations, it is evident that the integration of Maori culture into contemporary New Zealand has benefited the healthcare system. This unity has generated support for non-Western medical treatments, in turn forming a healthcare system that creates low barriers to entry for non-traditional forms of healthcare. These low barriers allow individuals to allocate available healthcare resources in ways that are most beneficial for them and are consistent with their tastes and preferences, maximizing efficiency.

Keywords: alternative and complementary healthcare, low barriers to entry, Maori populations, racial cohesion

Procedia PDF Downloads 198

Authors: Afzal Hussain, Mohammad A. Altamimi, Syed Sarim Imam, Mudassar Shahid, Osamah Abdulrahman Alnemer

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Exhaustive application of sulfamethoxazole (SUX) became as a global threat for human health due to water contamination through diverse sources. The addressed combined application of Hansen solubility (HSPiP software) parameters and Quality by Design tool for developing various green nanoemulsions. HSPiP program assisted to screen suitable excipients based on Hansen solubility parameters and experimental solubility data. Various green nanoemulsions were prepared and characterized for globular size, size distribution, zeta potential, and removal efficiency. Design Expert (DoE) software further helped to identify critical factors responsible to have direct impact on percent removal efficiency, size, and viscosity. Morphological investigation was visualized under transmission electron microscopy (TEM). Finally, the treated was studied to negate the presence of the tested drug employing ICP-OES (inductively coupled plasma optical emission microscopy) technique and HPLC (high performance liquid chromatography). Results showed that HSPiP predicted biocompatible lipid, safe surfactant (lecithin), and propylene glycol (PG). Experimental solubility of the drug in the predicted excipients were quite convincing and vindicated. Various green nanoemulsions were fabricated, and these were evaluated for in vitro findings. Globular size (100-300 nm), PDI (0.1-0.5), zeta potential (~ 25 mV), and removal efficiency (%RE = 70-98%) were found to be in acceptable range for deciding input factors with level in DoE. Experimental design tool assisted to identify the most critical variables controlling %RE and optimized content of nanoemulsion under set constraints. Dispersion time was varied from 5-30 min. Finally, ICP-OES and HPLC techniques corroborated the absence of SUX in the treated water. Thus, the strategy is simple, economic, selective, and efficient.

Keywords: quality by design, sulfamethoxazole, green nanoemulsion, water treatment, icp-oes, hansen program (hspip software

Procedia PDF Downloads 86

Authors: Imran Khan Swati, Mohammad Younas

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This work aims to explore the potential applications of polymeric hydrophobic membranes and green ionic liquids (ILs). Protic and aprotic ILs were synthesized in the lab., characterized, and tested for CO₂/N₂ and CO₂/CH₄ separation using hydrophobic polymeric membranes via supported ionic liquid membrane (SILM). ILs were verified by FTIR spectroscopy. The SILMs were stable at room temperature up to 0.5 MPa. For CO₂, [BSmim][tos] had the greatest coefficient of solubility and permeability, along with all ILs. At 0.5 MPa, IL [BSmim][tos] was found with a selectivity of 56.2 and 47.5 for pure CO₂/N₂ and CO₂/CH₄, respectively. The ILs synthesized for this study are rated as [BSmim][tos]>[BSmpy][tos]>[Bmim][Cl]>[Bpy][Cl] based on their SILM separation performance. Furthermore, high values of selectivity of [BSmim][tos] and [BSmpy][tos] support the use of ILs for CO₂ separation using SILMs. The study was extended to synthesize and test the ammonium-based ILs, [2-HEA][f] and [2-HEA][Hs]. These ILs achieved 50 % less selectivity for CO₂/N₂ as compared to [BSmim][tos] and [BSmpy][tos]. Nevertheless, the permeability of CO₂ achieved with [2-HEA][f] and [2-HEA][Hs] is more than 20 times higher than the [BSmim][tos] and [BSmpy][tos]. Later, the CO₂/N₂ permeability and selectivity study was extended using a flat sheet membrane contactor with recirculated IL. The contact angle effects, liquid entry pressure (LEP), initial CO₂ concentration, and type of solvents and membrane material on the CO₂ capture efficiency and membrane wetting in the post-combustion capture (PCC) process have been experimentally investigated and evaluated. Polytetrafluoroethylene (PTFE) has shown the most hydrophobic property with 6-170 loss in the contact angle. Furthermore, [Omim][BF4] and [Bmim][BF6] have exhibited only 5-8 % loss in LEP using PTFE membrane support. The CO₂ capture efficiency has been achieved as 80.8-99.8 % in different combinations of ILs and membrane support, keeping all other variables constant. While increasing CO₂ concentration from 15 to 45 % vol., an increase of nearly three folds in the CO₂ mass transfer flux was observed. The combination of [Omim][BF4] and PTFE membrane witnessed good long-term stability with only a 20 % loss in CO₂ capture efficiency in 480 min of continuous operation. A 3- D simulation model for non-dispersive solvent absorption in membrane contactors provides insight into the optimum design of a separation system for a specific application minimizing the overall cost and making the process environment-friendly.

Keywords: Post-combustion CO2 capture, membrane synthesis, process development, permeability and selectivity, ionic liquids

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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The Integrated Human Resources and Work Environment Management (HOWE) System optimises employee productivity, improves the work environment, and, at the same time, meets the employer’s strategic goals. The HOWE system has been designed to ensure an organisation can successfully compete in the global market, thanks to the high performance of its employees. The HOWE system focuses on raising workforce productivity and improving work conditions to boost employee performance and motivation. The methods used in our research are linear correlation, INVAR multiple criteria analysis, digital twin, and affective computing. The HOWE system is based on two patents issued in Lithuania (LT 6866, LT 6841) and one European Patent application (No: EP 4 020 134 A1). Our research analyses ways to make human resource management more efficient and boost labour productivity by improving and adapting a personalised work environment. The efficiency of human capital and labour productivity can be increased by applying personalised workplace improvement systems that can optimise lighting colours and intensity, scents, data, information, knowledge, activities, media, games, videos, music, air pollution, humidity, temperature, vibrations, and other workplace aspects. HOWE generates and maintains a personalised workspace for an employee, taking into account the person’s affective, physiological and emotional (APSE) states. The purpose of this project was to create a HOWE for the customisation of quality control in smart workspaces taking into account the user’s APSE states in an integrated manner as a single unit. This customised management of quality control covers the levels of lighting and colour intensities, scents, media, information, activities, learning materials, games, music, videos, temperature, energy efficiency, the carbon footprint of a workspace, humidity, air pollution, vibrations and other aspects of smart spaces. The system is based on Digital Twins technology, seen as a logical extension of BIM.

Keywords: human resource management, health economics, work environment, organizational behaviour and employee productivity, prosperity in work, smart system

Procedia PDF Downloads 77

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

Procedia PDF Downloads 65

Authors: R. Litt, A. Brown

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Aims: We aimed to assess the efficiency of ‘Attend Anywhere’ orthodontic clinics within a district general hospital during COVID- 19. Our secondary aim was to pilot a questionnaire to assess patient satisfaction with virtual orthodontic appointments. Design: The study design is a service evaluation including pilot questionnaire. Methods: The average number of patients seen per virtual clinic and the number of patients failing to attend was compared to face-to-face clinics. The capability of virtual appointments to be successful in preventing the need for a face-to-face appointment was assessed. Patients were invited to complete a telephone pilot questionnaire focusing on patient satisfaction and accessibility. Results: There was a small increase in the number of patients failing to attend virtual appointments, with a third of the patients who did not attend failing to receive the appointment link. 81.9% of virtual clinic appointments were successful and prevented the need for a face-to-face appointment. Overall patients were very satisfied with their virtual orthodontic appointment and the majority required no assistance to access the service. Conclusions: The use of ‘Attend Anywhere’ clinics in orthodontics offers patients and clinicians an effective and efficient alternative to face-to-face appointments that patients on average find easy to use and completely satisfactory.

Keywords: clinics, COVID, orthodontics, patient satisfaction, virtual

Procedia PDF Downloads 129

Authors: Sebastiano Candamano, Antonio Iorfida, Patrizia Frontera, Anastasia Macario, Fortunato Crea

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Alkali-activated materials are promising binders obtained by an alkaline attack on fly-ashes, metakaolin, blast slag among others. In order to guarantee the highest ecological and cost efficiency, a proper selection of precursors and alkaline activators has to be carried out. These choices deeply affect the microstructure, chemistry and performances of this class of materials. Even if, in the last years, several researches have been focused on mix designs and curing conditions, the lack of exhaustive activation models, standardized mix design and curing conditions and an insufficient investigation on shrinkage behavior, efflorescence, additives and durability prevent them from being perceived as an effective and reliable alternative to Portland. The aim of this study is to develop alkali-activated cements mortars containing high amounts of industrial by-products and waste, such as ground granulated blast furnace slag (GGBFS) and ashes obtained from the combustion process of forest biomass in thermal power plants. In particular, the experimental campaign was performed in two steps. In the first step, research was focused on elucidating how the workability, mechanical properties and shrinkage behavior of produced mortars are affected by the type and fraction of each precursor as well as by the composition of the activator solutions. In order to investigate the microstructures and reaction products, SEM and diffractometric analyses have been carried out. In the second step, their durability in harsh environments has been evaluated. Mortars obtained using only GGBFS as binder showed mechanical properties development and shrinkage behavior strictly dependent on SiO2/Na2O molar ratio of the activator solutions. Compressive strengths were in the range of 40-60 MPa after 28 days of curing at ambient temperature. Mortars obtained by partial replacement of GGBFS with metakaolin and forest biomass ash showed lower compressive strengths (≈35 MPa) and shrinkage values when higher amount of ashes were used. By varying the activator solutions and binder composition, compressive strength up to 70 MPa associated with shrinkage values of about 4200 microstrains were measured. Durability tests were conducted to assess the acid and thermal resistance of the different mortars. They all showed good resistance in a solution of 5%wt of H2SO4 also after 60 days of immersion, while they showed a decrease of mechanical properties in the range of 60-90% when exposed to thermal cycles up to 700°C.

Keywords: alkali activated cement, biomass ash, durability, shrinkage, slag

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Authors: M. Culman, O. Lengerke

Abstract:

To provide an efficient solar generation system, the embodiment design of a two axis solar tracker for an array of photovoltaic (PV) panels destiny to supply the power demand on off-the-grid areas was developed. Photovoltaic cells have high costs in relation to t low efficiency; and while a lot of research and investment has been made to increases its efficiency a few points, there is a profitable solution that increases by 30-40% the annual power production: two axis solar trackers. A solar tracker is a device that supports a load in a perpendicular position toward the sun during daylight. Mounted on solar trackers, the solar panels remain perpendicular to the incoming sunlight at day and seasons so the maximum amount of energy is outputted. Through a preview research done it was justified why the generation of solar energy through photovoltaic panels mounted on dual axis structures is an attractive solution to bring electricity to remote off-the-grid areas. The work results are the embodiment design of an azimuth-altitude solar tracker to guide an array of photovoltaic panels based on a specific design methodology. The designed solar tracker is mounted on a pedestal that uses two slewing drives‚ with a nominal torque of 1950 Nm‚ to move a solar array that provides 3720 W from 12 PV panels.

Keywords: azimuth-altitude sun tracker, dual-axis solar tracker, photovoltaic system, solar energy, stand-alone power system

Procedia PDF Downloads 263

Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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Changes in behaviour and physiology are the most important responses of marine life to anthropogenic impacts such as climate change and over-fishing. Behavioural changes (such as a shift in distribution or changes in phenology) can ensure that a species remains in an environment suited for its optimal physiological performance. However, if marine life is unable to shift their distribution, they are reliant on physiological adaptation (either by broadening their metabolic curves to tolerate a range of stressors or by shifting their metabolic curves to maximize their performance at extreme stressors). However, since there are links between fish physiology and behaviour, changes to either of these traits may have reciprocal interactions. This paper reviews the current knowledge of the links between the behaviour and physiology of fishes, discusses these in the context of exploitation and climate change, and makes recommendations for future research needs. The review revealed that our understanding of the links between fish behaviour and physiology is rudimentary. However, both are hypothesized to be linked to stress responses along the hypothalamic pituitary axis. The link between physiological capacity and behaviour is particularly important as both determine the response of an individual to a changing climate and are under selection by fisheries. While it appears that all types of capture fisheries are likely to reduce the adaptive potential of fished populations to climate stressors, angling, which is primarily associated with recreational fishing, may induce fission of natural populations by removing individuals with bold behavioural traits and potentially the physiological traits required to facilitate behavioural change. Future research should focus on assessing how the links between physiological capacity and behaviour influence catchability, the response to climate change drivers, and post-release recovery. The plasticity of phenotypic traits should be examined under a range of stressors of differing intensity in several species and life history stages. Future studies should also assess plasticity (fission or fusion) in the phenotypic structuring of social hierarchy and how this influences habitat selection. Ultimately, to fully understand how physiology is influenced by the selective processes driven by fisheries, long-term monitoring of the physiological and behavioural structure of fished populations, their fitness, and catch rates are required.

Keywords: climate change, metabolic shifts, over-fishing, phenotypic plasticity, stress response

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Authors: Henry R. Troy

Abstract:

Corpora are becoming more prevalent in the language classroom, especially in the development of dictionaries and course materials. Nevertheless, corpora are still perceived by many educators as difficult to use directly in the classroom, a process which is also known as “data-driven learning” (DDL). Action research has been identified as a method by which DDL’s efficiency can be increased, but it is also an approach few studies on DDL have employed. Studies into the effectiveness of DDL in language education in Japan are also rare, and investigations focused more on student and teacher reactions rather than pre and post-test scores are rarer still. This study investigates the student and teacher reactions to the use of SkELL, a free online corpus designed to be user-friendly, for vocabulary learning at a university in Japan. Action research is utilized to refine the teaching methodology, with changes to the method based on student and teacher feedback received via surveys submitted after each of the four implementations of DDL. After some training, the students used tablets to study the target vocabulary autonomously in pairs and groups, with the teacher acting as facilitator. The results show that the students enjoyed using SkELL and felt it was effective for vocabulary learning, while the teaching methodology grew in efficiency throughout the course. These findings suggest that action research can be a successful method for increasing the efficacy of DDL in the language classroom, especially with teachers and students who are new to the practice.

Keywords: action research, corpus linguistics, data-driven learning, vocabulary learning

Procedia PDF Downloads 258

Authors: Abdelkader T. Ahmed

Abstract:

Greywater is any wastewater draining from a household including kitchen sinks and bathroom tubs, except toilet wastes. Although this used water may contain grease, food particles, hair, and any number of other impurities, it may still be suitable for reuse after treatment. Greywater reusing serves two purposes including reduction the amount of freshwater needed to supply a household, and reduction the amount of wastewater entering sewer systems. This study aims to investigate and design a simple and cheap unit to treat the greywater in household via using ceramic membranes and reuse it in supplying water for toilet flushing. The study include an experimental program for manufacturing several tablet ceramic membranes from clay and sawdust with three different mixtures. The productivity and efficiency of these ceramic membranes were investigated by chemical and physical tests for greywater before and after filtration through these membranes. Then a treatment unit from this ceramic membrane was designed based on the experimental results of lab tests. Results showed that increase sawdust percent with the mixture increase the flow rate and productivity of treated water but decrease in the same time the water quality. The efficiency of the new ceramic membrane reached 95%. The treatment unit save 0.3 m3/day water for toilet flushing without need to consume them from the fresh water supply network.

Keywords: ceramic membranes, filtration, greywater, wastewater treatment

Procedia PDF Downloads 334

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

Procedia PDF Downloads 45

Authors: Osarobo Omorogieva Ighodaro, Josephus Otejere

Abstract:

This paper contains the modelling and simulation of GT13E2 combined cycle gas turbine with the aid of the software EBSILON PROFESSIONAL. The design mode was modeled using guaranteed performance data from the power plant, in the off design, temperature variation of ambient air and fogging (spray water at inlet to compressor) was simulated. The fogging was simulated under two different modes; constant fuel consumption and constant turbine exhaust temperature .The model results were validated using actual operating data by applying error percentage analysis. The validation results obtained ranged from -0.0038% to 0% in design condition while the results varied from -0.9202% to 10.24% The model shows that fogging decreases compressor inlet temperature which in turn decreases the power required to drive the compressor hence improving the simple cycle efficiency and hence increasing power generated.

Keywords: inlet fogging, off design, combined cycle, modelling

Procedia PDF Downloads 45

Authors: P. Lestinsky, D. Jecha, V. Brummer, P. Stehlik

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Scrubbing by a liquid spraying is one of the most effective processes used for removal of fine particles and soluble gas pollutants (such as SO2, HCl, HF) from the flue gas. There are many configurations of scrubbers designed to provide contact between the liquid and gas stream for effectively capturing particles or soluble gas pollutants, such as spray plates, packed bed towers, jet scrubbers, cyclones, vortex and venturi scrubbers. The primary function of venturi scrubber is the capture of fine particles as well as HCl, HF or SO2 removal with effect of the flue gas temperature decrease before input to the absorption column. In this paper, sulfur dioxide (SO2) from flue gas was captured using new design replacing venturi scrubber (1st degree of wet scrubbing). The flue gas was prepared by the combustion of the carbon disulfide solution in toluene (1:1 vol.) in the flame in the reactor. Such prepared flue gas with temperature around 150 °C was processed in designed laboratory O-element scrubber. Water was used as absorbent liquid. The efficiency of SO2 removal, pressure drop and temperature drop were measured on our experimental device. The dependence of these variables on liquid-gas ratio was observed. The average temperature drop was in the range from 150 °C to 40 °C. The pressure drop was increased with increasing of a liquid-gas ratio, but not as much as for the common venturi scrubber designs. The efficiency of SO2 removal was up to 70 %. The pressure drop of our new designed wet scrubber is similar to commonly used venturi scrubbers; nevertheless the influence of amount of the liquid on pressure drop is not so significant.

Keywords: desulphurization, absorption, flue gas, modeling

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Authors: Shubham Jaiswal

Abstract:

During modeling of transport phenomena in porous media, many nonlinear partial differential equations (NPDEs) encountered which greatly described the convection, diffusion and reaction process. To solve such types of nonlinear problems, a reliable and efficient technique is needed. In this article, the numerical solution of NPDEs encountered in porous media is derived. Here Jacobi collocation method is used to solve the considered problems which convert the NPDEs in systems of nonlinear algebraic equations that can be solved using Newton-Raphson method. The numerical results of some illustrative examples are reported to show the efficiency and high accuracy of the proposed approach. The comparison of the numerical results with the existing analytical results already reported in the literature and the error analysis for each example exhibited through graphs and tables confirms the exponential convergence rate of the proposed method.

Keywords: nonlinear porous media equation, shifted Jacobi polynomials, operational matrix, spectral collocation method

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Authors: Lucas Aerre, Wallesson Faria, Roberto Pimentel, Juliana Santos

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An extremely disturbing and irritating element in the lives of people and organizations is the noise, the consequences that can bring us has a lot of connection with human health as well as financial and economic aspects. In order to improve the efficiency of buildings in Brazil in general, a performance standard was created, NBR 15.575 in which all buildings are seen in a more systemic and peculiar way, while following the requirements of the standard. The acoustic performance present in these buildings is one such requirement. Based on this, the present work was elaborated with the objective of evaluating through acoustic measurements the acoustic performance of vertical internal fences that are under the incidence of aerial noise of a building in the city of Brasilia-DF. A short theoretical basis is made and soon after the procedures of measurement are described through the control method established by the standard, and its results are evaluated according to the parameters of the same. The measurement performed between rooms of the same unit, presented a standardized sound pressure level difference (D nT, w) equal to 40 dB, thus being classified within the minimum performance required by the standard in question.

Keywords: airborne noise, performance standard, soundproofing, vertical seal

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Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

Procedia PDF Downloads 273

Authors: Weerinda Appamana, Jirapong Keawkoon, Yamonporn Pacthong, Jirathiti Chitsanguansuk, Yanyong Sookklay

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In the present work, spinning disc reactor has been used for the intensification of synthesis of biodiesel from refined palm oil (RPO) based on the transesterification reaction. Experiments have been performed using different spinning disc surface and under varying operating parameters viz. molar ratio of oil to methanol (over the range of 1:4.5–1:9), rotational speed (over the range of 500–2,000 rpm), total flow rate (over the range of 260-520 ml/min), and KOH catalyst loading of 1.50% by weight of oil. Maximum FAME (fatty acid methyl esters) yield (97.5 %) of biodiesel from RPO was obtained at oil to methanol ratio of 1:6, temperature of 60 °C, and rotational speed of 1500 rpm and flow rate of 520 mL/min using groove disc at KOH catalyst loading of 1.5 wt%. Also, higher yield efficiency (biodiesel produced per unit energy consumed) was obtained for using the spinning disc reactor based approach as compared to the ultrasound hydrodynamic cavitation and conventional mechanical stirrer reactors. It obviously offers a significant reduction in the reaction time for the transesterification, especially when compared with the reaction time of 90 minutes required for the conventional mechanical stirrer. It can be concluded that the spinning disk reactor is a promising alternative method for continuous biodiesel production.

Keywords: spinning disc reactor, biodiesel, process intensification, yield efficiency

Procedia PDF Downloads 159

Authors: Parthiban S. R.

Abstract:

Spiral heat exchangers are known as excellent heat exchanger because of far compact and high heat transfer efficiency. An innovative spiral heat exchanger based on polymer materials is designed for waste heat recovery process. Such a design based on polymer film technology provides better corrosion and chemical resistance compared to conventional metal heat exchangers. Due to the smooth surface of polymer film fouling is reduced. A new arrangement for flow of hot flue gas and cold fluid is employed for design, flue gas flows in axial path while the cold fluid flows in a spiral path. Heat load recovery achieved with the presented heat exchanger is in the range of 1.5 kW thermic but potential heat recovery about 3.5 kW might be achievable. To measure the performance of the spiral tube heat exchanger, its model is suitably designed and fabricated so as to perform experimental tests. The paper gives analysis of spiral tube heat exchanger.

Keywords: spiral heat exchanger, polymer based materials, fouling factor, heat load

Procedia PDF Downloads 397

Authors: Leonardo C. Pacheco-Londoño, Nataly J Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta-Hoyos, Elkin Navarro, Gustavo Aroca-Martinez, Karin Rondón-Payares, Alberto C. Espinosa-Garavito, Samuel P. Hernández-Rivera

Abstract:

At the Life Science Research Center at Simon Bolivar University, a primary focus is the diagnosis of various diseases, and the use of gold nanoparticles (Au-NPs) in diverse biomedical applications is continually expanding. In the present study, Au-NPs were employed as substrates for Surface-Enhanced Raman Spectroscopy (SERS) aimed at diagnosing kidney diseases arising from Lupus Nephritis (LN), preeclampsia (PC), and Hypertension (H). Discrimination models were developed for distinguishing patients with and without kidney diseases based on the SERS signals from urine samples by partial least squares-discriminant analysis (PLS-DA). A comparative study of the Raman signals across the three conditions was conducted, leading to the identification of potential metabolite signals. Model performance was assessed through cross-validation and external validation, determining parameters like sensitivity and specificity. Additionally, a secondary analysis was performed using machine learning (ML) models, wherein different ML algorithms were evaluated for their efficiency. Models’ validation was carried out using cross-validation and external validation, and other parameters were determined, such as sensitivity and specificity; the models showed average values of 0.9 for both parameters. Additionally, it is not possible to highlight this collaborative effort involved two university research centers and two healthcare institutions, ensuring ethical treatment and informed consent of patient samples.

Keywords: SERS, Raman, PLS-DA, kidney diseases

Procedia PDF Downloads 51

Authors: Young-Hun Lee, Tae-Gwan Kim, Jong-Kyu Kim, Young-Chul Park

Abstract:

In this study, Spring safety valve Heat - structure coupled analysis was carried out. Full analysis procedure and performing thermal analysis at a maximum temperature, them to the results obtained through to give an additional load and the pressure on the valve interior, and Disc holder Heat-Coupled structure Analysis was carried out. Modeled using a 3D design program Solidworks, For the modeling of the safety valve was used 3D finite element analysis program ANSYS. The final result to be obtained through the Analysis examined the stability of the maximum displacement and the maximum stress to the valve internal components occurring in the high-pressure conditions.

Keywords: finite element method, spring safety valve, gap, stress, strain, deformation

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

Abstract:

The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: dynamic algorithm, load imbalance, mapping, task scheduling

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Authors: Salomão Manuel Francisco, Manuel António Salgueiro Da Silva, Bento Filipe Barreiras Pinto Cavadas, Teresa Monteiro Seixas

Abstract:

In bachelor's degrees in Physics Education framework in Angola, and to a certain extent, within the community of Portuguese language countries (CPLP), teaching methodologies rely heavily on theoretical memorization and mathematical demonstrations. This approach often discourages students, particularly the female population, as the reliance on theoretical mathematical demonstrations generates the perception of Physics as an arduous, challenging discipline. To address this challenge and recognize the value of practical application as an evaluative criterion of material truth, we propose a practical activity in Environmental Physics that will be shared with Angolan higher education teachers, who will receive full scaffolding and support from the authors. These teachers, adopting and developing similar activities in a classroom setting, will contribute to the environmental education framework as well. Additionally, this work aligns with different goals of UNESCO's 2030 agenda, namely, specifically, goals 4, 5, 7, 11, 13, and 17. The experimental activity developed in this work is centered around the demonstration of the photovoltaic effect and its application for renewable energy production. The first objective of the activity is to study the variation of electrical power supplied by a photovoltaic system (PV) to an electrical circuit as the angle of light incidence changes. Students can observe that the power supplied to the circuit is greater when light rays fall perpendicularly on the PV. However, as the angle of incidence increases, resulting in a larger area covered by the light rays, the power supplied to the circuit decreases due to lower irradiance. The second objective is to demonstrate that the power output can be maximized by adjusting the circuit load resistance at each irradiance value. In these two parts of the activity, students can analyze experimental data taking into account the irradiance law and the equivalent circuit description of a PV cell. Through detailed data analysis, students are also expected to assess the effects of temperature on PV efficiency degradation and the efficiency enhancement provided by light concentration mechanisms. As a third objective, students can explore how the color of incident light affects the PV output power, considering the quantum nature of light and its interaction with the PV system.

Keywords: experiments, irradiation law, physic teaching, photovoltaic effect

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Authors: Tsegaye Adane Birhan

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Recently, rapid industrialization has led to the excessive release of heavy metals such as Cr (VI) into the environment. Exposure to chromium (VI) can cause kidney and liver damage, depressed immune systems, and a variety of cancers. Therefore, treatment of Cr (VI) containing wastewater is mandatory. This study aims to optimize the removal of Cr (VI) from an aqueous solution using locally available Teff husk-activated carbon adsorbent. The laboratory-based study was conducted on the optimization of Cr (VI) removal efficiency of Teff husk-activated carbon from aqueous solution. A central composite design was used to examine the effect of the interaction of process parameters and to optimize the process using Design Expert version 7.0 software. The optimized removal efficiency of Teff husk activated carbon (95.597%) was achieved at 1.92 pH, 87.83mg/L initial concentration, 20.22g/L adsorbent dose and 2.07Hrs contact time. The adsorption of Cr (VI) on Teff husk-activated carbon was found to be best fitted with pseudo-second-order kinetics and Langmuir isotherm model of the adsorption. Teff husk-activated carbon can be used as an efficient adsorbent for the removal of chromium (VI) from contaminated water. Column adsorption needs to be studied in the future.

Keywords: batch adsorption, chromium (VI), teff husk activated carbon, response surface methodology, tannery wastewater

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Authors: Coriolano Salvini, Ambra Giovannelli

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The use of renewable energy sources for electric power production leads to reduced CO2 emissions and contributes to improving the domestic energy security. On the other hand, the intermittency and unpredictability of their availability poses relevant problems in fulfilling safely and in a cost efficient way the load demand along the time. Significant benefits in terms of “grid system applications”, “end-use applications” and “renewable applications” can be achieved by introducing energy storage systems. Among the currently available solutions, CAES (Compressed Air Energy Storage) shows favorable features. Small-medium size plants equipped with artificial air reservoirs can constitute an interesting option to get efficient and cost-effective distributed energy storage systems. The present paper is addressed to the design and off-design analysis of the compression system of small size CAES plants suited to absorb electric power in the range of hundreds of kilowatt. The system of interest is constituted by an intercooled (in case aftercooled) multi-stage reciprocating compressor and a man-made reservoir obtained by connecting large diameter steel pipe sections. A specific methodology for the system preliminary sizing and off-design modeling has been developed. Since during the charging phase the electric power absorbed along the time has to change according to the peculiar CAES requirements and the pressure ratio increases continuously during the filling of the reservoir, the compressor has to work at variable mass flow rate. In order to ensure an appropriately wide range of operations, particular attention has been paid to the selection of the most suitable compressor capacity control device. Given the capacity regulation margin of the compressor and the actual level of charge of the reservoir, the proposed approach allows the instant-by-instant evaluation of minimum and maximum electric power absorbable from the grid. The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way. Various cases characterized by different system requirements are analysed. Results are given and widely discussed.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), compressor design, compression system management.

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Authors: Norashikin Ismail, Nadia Anridho

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Sustainable investing is a responsible investment that focuses on Environmental, Social, and Governance (ESG) elements. ESG integration is essential in the investment process as it provides a positive contribution to the corporate performance for stakeholders, specifically investors. Sustainable investing is in line with the objectives of Shariah (Maqasid of Shariah), such as social inclusion as well as environmental preservation. This study attempts to evaluate the impact of ESG elements to the corporate financial performance among Shariah compliant stocks listed in two countries, namely Malaysia and Indonesia. The motivation of this study is to provide a further understanding in corporate sustainability for two different Islamic capital markets. The existence of the FTSE4Good Asean Index has played a vital role for ESG practices and eventually encouraged specific index for ESG and Shariah Compliant stocks. Our sample consists of 60 companies over the period 2010-2020 from two Southeast countries. We employ System Generalized Method of Moments (GMM) to reduce bias and more specific parameter estimation. Shariah Compliant companies tend to have higher ESG scores and are positively correlated to corporate financial performance. ESG integration with Shariah based investing would provide higher returns and lower risks for Muslim investors. Essentially, integrating ESG and Shariah, compliant companies lead to better financial performance.

Keywords: shariah compliant, southeast asia, corporate performance, sustainable investing

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Authors: Mohamed Ali Abdennadher

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Digital rock physics, an emerging field leveraging advanced imaging and numerical techniques, offers a promising approach to investigating the mechanical properties of granular materials without extensive physical experiments. This study focuses on using X-Ray Computed Tomography (CT) to capture the three-dimensional (3D) structure of coarse-grained soil at the particle level, combined with finite element analysis (FEA) to simulate the soil's behavior under compression. The primary goal is to establish a reliable virtual testing framework that can replicate laboratory results and offer deeper insights into soil mechanics. The methodology involves acquiring high-resolution CT scans of coarse-grained soil samples to visualize internal particle morphology. These CT images undergo processing through noise reduction, thresholding, and watershed segmentation techniques to isolate individual particles, preparing the data for subsequent analysis. A custom Python script is employed to extract particle shapes and conduct a statistical analysis of particle size distribution. The processed particle data then serves as the basis for creating a finite element model comprising approximately 500 particles subjected to one-dimensional compression. The FEA simulations explore the effects of mesh refinement and friction coefficient on stress distribution at grain contacts. A multi-layer meshing strategy is applied, featuring finer meshes at inter-particle contacts to accurately capture mechanical interactions and coarser meshes within particle interiors to optimize computational efficiency. Despite the known challenges in parallelizing FEA to high core counts, this study demonstrates that an appropriate domain-level parallelization strategy can achieve significant scalability, allowing simulations to extend to very high core counts. The results show a strong correlation between the finite element simulations and laboratory compression test data, validating the effectiveness of the virtual experiment approach. Detailed stress distribution patterns reveal that soil compression behavior is significantly influenced by frictional interactions, with frictional sliding, rotation, and rolling at inter-particle contacts being the primary deformation modes under low to intermediate confining pressures. These findings highlight that CT data analysis combined with numerical simulations offers a robust method for approximating soil behavior, potentially reducing the need for physical laboratory experiments.

Keywords: X-Ray computed tomography, finite element analysis, soil compression behavior, particle morphology

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Authors: Muhammad Muzamil Khan, Asadullah Madni, Nina Filipczek, Jiayi Pan, Nayab Tahir, Hassan Shah, Vladimir Torchilin

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Lipid-polymer hybrid nanoparticles (LPHNP) are delivery systems for controlled drug delivery at tumor sites. The superior biocompatible properties of lipid and structural advantages of polymer can be obtained via this system for controlled drug delivery. In the present study, cisplatin-loaded lipid-chitosan hybrid nanoparticles were formulated by the single step ionic gelation method based on ionic interaction of positively charged chitosan and negatively charged lipid. Formulations with various chitosan to lipid ratio were investigated to obtain the optimal particle size, encapsulation efficiency, and controlled release pattern. Transmission electron microscope and dynamic light scattering analysis demonstrated a size range of 181-245 nm and a zeta potential range of 20-30 mV. Compatibility among the components and the stability of formulation were demonstrated with FTIR analysis and thermal studies, respectively. The therapeutic efficacy and cellular interaction of cisplatin-loaded LPHNP were investigated using in vitro cell-based assays in A2780/ADR ovarian carcinoma cell line. Additionally, the cisplatin loaded LPHNP exhibited a low toxicity profile in rats. The in-vivo pharmacokinetics study also proved a controlled delivery of cisplatin with enhanced mean residual time and half-life. Our studies suggested that the cisplatin-loaded LPHNP being a promising platform for controlled delivery of cisplatin in cancer therapy.

Keywords: cisplatin, lipid-polymer hybrid nanoparticle, chitosan, in vitro cell line study

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Authors: Herviyanti, Gusnidar, M. Harianti

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The objective of this research were: a) using low-rank coal (subbituminous) as main humate material sources because this material will not be anthracite, and cannot using to be an energy sources b) to examine residual effects of humic matter from subbituminous which was combined with P fertilizers to adsorp Al and Fe metal, improving soil fertility, and increasing P fertilizing efficiency and Oxisol productivity. Therefore, optimalization crop productivity of upland rice can be achieved. The experiment was designed using a 3 x 4 factorial with 3 replications in randomly groups design. The 1st factor was 3 ways incubating humate material with P-fertilizer, which are: I1 = Incubation of humate material 1 week, then incubation P-fertilizers 1 week; I2 = Incubation of humate materials and P fertilizers directly into the soil for 2 weeks; and I3 = humate material and P fertilizer mixed for 1 week, then incubation to the soil for 1 week. The 2nd factor was residual effects of humate material and P-fertilizer combination which are 4 doses H1 = 400 ppm (0.8 Mg/ha) + 100% R; H2 = 400 ppm + 75% R; H3 = 800 ppm (1.6 Mg/ha) + 100% R,; and H4 = 800 ppm + 75% R. The 2nd year research results showed that the best treatment was founded residue effect of 800 ppm humate material and 100% R P-fertilizer doses in I3 way incubation that is equal to 6.19 t ha-1 upland rice yield. However, this result is almost the same as residual effects of 800 ppm humate material + 75% R P-fertilizer doses and upland rice yield the 1st year. It was concluded that addition of humate material can given the efficiency of P-fertilizer using up to 25% until the 2nd season planted.

Keywords: humate materials, P-fertilizer, subbituminous, upland rice

Procedia PDF Downloads 397